Gossip-based solutions for discrete rendezvous in populations of communicating agents.

Hollander CD, Wu AS - PLoS ONE (2014)

Bottom Line:
The objective of the rendezvous problem is to construct a method that enables a population of agents to agree on a spatial (and possibly temporal) meeting location.We use these results to verify that the uniform gossip algorithm also solves the rendezvous problem.We then use a multi-agent simulation to conduct a series of simulation experiments to compare the performance between the buffered and uniform gossip algorithms.

Affiliation: Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL, United States of America.

ABSTRACTThe objective of the rendezvous problem is to construct a method that enables a population of agents to agree on a spatial (and possibly temporal) meeting location. We introduce the buffered gossip algorithm as a general solution to the rendezvous problem in a discrete domain with direct communication between decentralized agents. We compare the performance of the buffered gossip algorithm against the well known uniform gossip algorithm. We believe that a buffered solution is preferable to an unbuffered solution, such as the uniform gossip algorithm, because the use of a buffer allows an agent to use multiple information sources when determining its desired rendezvous point, and that access to multiple information sources may improve agent decision making by reinforcing or contradicting an initial choice. To show that the buffered gossip algorithm is an actual solution for the rendezvous problem, we construct a theoretical proof of convergence and derive the conditions under which the buffered gossip algorithm is guaranteed to produce a consensus on rendezvous location. We use these results to verify that the uniform gossip algorithm also solves the rendezvous problem. We then use a multi-agent simulation to conduct a series of simulation experiments to compare the performance between the buffered and uniform gossip algorithms. Our results suggest that the buffered gossip algorithm can solve the rendezvous problem faster than the uniform gossip algorithm; however, the relative performance between these two solutions depends on the specific constraints of the problem and the parameters of the buffered gossip algorithm.

pone-0112612-g004: Box plots for the rendezvous time on Barabasi-Albert scale-free networks showing the interquartile range, median value, and outliers.It can be observed that buffered gossip algorithms using maximum frequency selection generally have a lower rendezvous time than the tested alternatives.

Mentions:
Figure 4 visualizes our experimental data from 300 randomly generated Barabasi-Albert scale-free networks using a standard box plot. The x-axis indicates the state update protocol used by each algorithm. The y-axis indicates the number of steps until consensus is achieved. The y-axis has been transformed logarithmically in order to improve the overall visualization of the data; the data itself has not been transformed. We observe that a buffered gossip algorithm using maximum frequency selection has the lowest median rendezvous time and smallest third quartile. These observations suggest that, when agents communicate over Barabasi-Albert scale-free networks, a buffered gossip algorithm using maximum frequency selection should produce lower rendezvous times in comparison to a buffered gossip algorithm using proportional selection or the uniform gossip algorithm.

pone-0112612-g004: Box plots for the rendezvous time on Barabasi-Albert scale-free networks showing the interquartile range, median value, and outliers.It can be observed that buffered gossip algorithms using maximum frequency selection generally have a lower rendezvous time than the tested alternatives.

Mentions:
Figure 4 visualizes our experimental data from 300 randomly generated Barabasi-Albert scale-free networks using a standard box plot. The x-axis indicates the state update protocol used by each algorithm. The y-axis indicates the number of steps until consensus is achieved. The y-axis has been transformed logarithmically in order to improve the overall visualization of the data; the data itself has not been transformed. We observe that a buffered gossip algorithm using maximum frequency selection has the lowest median rendezvous time and smallest third quartile. These observations suggest that, when agents communicate over Barabasi-Albert scale-free networks, a buffered gossip algorithm using maximum frequency selection should produce lower rendezvous times in comparison to a buffered gossip algorithm using proportional selection or the uniform gossip algorithm.

Bottom Line:
The objective of the rendezvous problem is to construct a method that enables a population of agents to agree on a spatial (and possibly temporal) meeting location.We use these results to verify that the uniform gossip algorithm also solves the rendezvous problem.We then use a multi-agent simulation to conduct a series of simulation experiments to compare the performance between the buffered and uniform gossip algorithms.

Affiliation:
Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL, United States of America.

ABSTRACTThe objective of the rendezvous problem is to construct a method that enables a population of agents to agree on a spatial (and possibly temporal) meeting location. We introduce the buffered gossip algorithm as a general solution to the rendezvous problem in a discrete domain with direct communication between decentralized agents. We compare the performance of the buffered gossip algorithm against the well known uniform gossip algorithm. We believe that a buffered solution is preferable to an unbuffered solution, such as the uniform gossip algorithm, because the use of a buffer allows an agent to use multiple information sources when determining its desired rendezvous point, and that access to multiple information sources may improve agent decision making by reinforcing or contradicting an initial choice. To show that the buffered gossip algorithm is an actual solution for the rendezvous problem, we construct a theoretical proof of convergence and derive the conditions under which the buffered gossip algorithm is guaranteed to produce a consensus on rendezvous location. We use these results to verify that the uniform gossip algorithm also solves the rendezvous problem. We then use a multi-agent simulation to conduct a series of simulation experiments to compare the performance between the buffered and uniform gossip algorithms. Our results suggest that the buffered gossip algorithm can solve the rendezvous problem faster than the uniform gossip algorithm; however, the relative performance between these two solutions depends on the specific constraints of the problem and the parameters of the buffered gossip algorithm.